An exciting world within Big Data
Machine Learning (ML) is an area of knowledge within Artificial Intelligence (AI) where computers apply statistical learning techniques with the purpose of automatically identifying patterns in the data. The generated algorithms are able to generalize behaviors from the data provided in the form of examples.
The main feature of ML algorithms is that they are able to readjust automatically to improve their performance based on the number of hits and failures produced in a training process prior to its application and, during the real-time execution of it.
Supervised Learning
Its goal is to predict future responses thanks to the training the algorithm receives through past data. It's defined by its use of labeled datasets.
Unsupervised Learning
It focuses on testing and determining the existing structure in the data. It analyzes and groups unlabeled data sets.
Reinforcement Learning
It focuses on rule-based learning processes capable of learning from your environment, in which ML algorithms are provided with information about what is or is not appropriate.
Anomaly Detection
A solution to an unsupervised learning problem, that also has aspects of supervised learning. It can help you prevent fraud, attacks, and network intrusions that can compromise your company's future.